Schedule optimization and staff allocation for airport security checkpoints using guided simulated annealing and integer linear programming

Abstract

Security checkpoints are an important matter of concern for airport operators. When functioning effectively, they not only maintain the airport overall safety at a high level, but also provide passengers with a positive airport experience. The perceived quality of service at the airport greatly depends on the time spent by passengers at the security lines. To ensure optimal safety performance, screening lines have a limited capacity of passengers they can handle. Thus, to prevent extended waiting times for passengers, airports can only adjust the number of simultaneously open check lines. The airport operator must establish optimal schedules for opening security checkpoints and allocating necessary staff. Building upon a prior study focused on predicting the flow of passengers through the security checkpoints, this paper explores simulated annealing algorithm in conjunction with a queue simulator and an integer programming algorithm to establish the most effective opening schedule for security checkpoints based on the prediction given by this previous study. The presented approach also determines the best allocation for dedicated staff based on the forecasted passenger flow. This approach limits the number of open security lines and ensures a waiting time below the maximum limit of 45 min set by the airport. It also complies with the work regulations that security agents are subject to.